Evidence map›Paper›PMID 35037102›Full record

ArticleJournal of cancer research and clinical oncology2022

Mammographic density to predict response to neoadjuvant systemic breast cancer therapy.

S Di Cosimo, C Depretto, R Miceli, P Baili, S Ljevar, M Sant, V Cappelletti, S Folli, M Gennaro, F G De Braud and 7 more

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 1 institution in 1 country.

S Di Cosimo *Biomarkers Unit, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
C Depretto *Radiology Unit, Fondazione IRCCS, Istituto Nazionale Tumori, Milano, Italy.
R MiceliDepartment of Clinical Epidemiology and Trial Organisation, Fondazione IRCCS Istituto Nazionale Tumori, Milano, Italy.
P BailiAnalytical Epidemiology and Health Impact Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
S LjevarDepartment of Clinical Epidemiology and Trial Organisation, Fondazione IRCCS Istituto Nazionale Tumori, Milano, Italy.
M SantAnalytical Epidemiology and Health Impact Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
V CappellettiBiomarkers Unit, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
S FolliBreast Surgery Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
M GennaroBreast Surgery Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
F G De BraudDivision of Medical Oncology 1, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
G BianchiDivision of Medical Oncology 1, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
A VingianiDepartment of Pathology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
G PruneriDepartment of Pathology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.
A MarchianòRadiology Unit, Fondazione IRCCS, Istituto Nazionale Tumori, Milano, Italy.
E La RoccaRadiation Oncology 1, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Venezian 1, 20100, Milano, Italy.
M C De SantisRadiation Oncology 1, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Venezian 1, 20100, Milano, Italy. mariacarmen.desantis@istitutotumori.mi.it.ORCID http://orcid.org/0000-0003-3131-3969
G P ScaperrottaRadiology Unit, Fondazione IRCCS, Istituto Nazionale Tumori, Milano, Italy.
Fondazione IRCCS Istituto Nazionale dei Tumori · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMammographic density (MD) is a risk factor for breast cancer (BC) development, and recurrence. However, its predictive value has been less studied. Herein, we challenged MD as a biomarker associated with response in patients treated with neoadjuvant therapy (NAT).

methodsData on all NAT treated BC patients prospectively collected in the registry of Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy (2009-2019) were identified. Diagnostic mammograms were used to evaluate and score MD as categorized by the Breast Imaging-Reporting and Data System (BI-RADS), which identifies 4 levels of MD in keeping with relative increase of fibro-glandular over fat tissue. Each case was classified according to the following categories a (MD < 25%), b (26-50%), c (51-75%), and d (> 75%). The association between MD and pathological complete response (pCR), i.e., absence of BC cells in surgical specimens, was analyzed in multivariable setting used logistic regression models with adjustment for clinical and pathological variables.

resultsA total of 442 patients were analyzed, 120 of which (27.1%) attained a pCR. BI-RADS categories a, b, c, and d accounted for 10.0%, 37.8%, 37.1% and 15.2% of cases. Corresponding pCR were 20.5%, 26.9%, 30.5%, 23.9%, respectively. At multivariable analysis, when compared to cases classified as BI-RADS a, those with denser breast showed an increased likelihood of pCR with odds ratio (OR) of 1.70, 2.79, and 1.47 for b, c and d categories, respectively (p = 0.0996), independently of age, BMI [OR underweight versus (vs) normal = 3.76], clinical nodal and tumor status (OR T1/Tx vs T4 = 3.87), molecular subtype (HER2-positive vs luminal = 10.74; triple-negative vs luminal = 8.19). In subgroup analyses, the association of MD with pCR was remarkable in triple-negative (ORs of b, c and d versus a: 1.85, 2.49 and 1.55, respectively) and HER2-positive BC cases (ORs 2.70, 3.23, and 1.16).

conclusionPatients with dense breast are more likely to attain a pCR at net of other predictive factors. The potential of MD to assist decisions on BC management and as a stratification factor in neoadjuvant clinical trials should be considered.

Indexed as

Breast DensityBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesFemaleHumansMammographyNeoadjuvant TherapyOdds RatioErb-b2 Receptor Tyrosine KinasesBreast cancerMammographic densityMedical subject headings (MeSH)Neoadjuvant therapyPathological complete response

Identifiers

PMID35037102
PMCPMC11800836
OpenAlexW4206756322

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.